Information spreading by a combination of MEG source estimation and multivariate pattern classification.
Information spreading by a combination of MEG source estimation and multivariate pattern classification.
复制标题
信息通过MEG来源估计和多元模式分类的组合扩散。
DOI：
10.1371/journal.pone.0198806
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发表时间：
2018
期刊：
影响因子：
3.7
通讯作者：
Miyawaki Y
中科院分区：
文献类型：
--
作者：
Sato M;Yamashita O;Sato MA;Miyawaki Y
为了理解人类大脑活动中的信息表征，重要的是在高时间分辨率下研究其精细的空间模式。一种可能的方法是使用脑磁图（MEG）信号的源估计。以前的研究主要是量化的准确性，这种技术根据位置偏差和分散的估计源，但它仍然不清楚如何准确地MEG源估计恢复信息内容所代表的空间模式的大脑活动。在这项研究中，使用模拟MEG信号代表人工实验条件下，我们进行MEG源估计和多元模式分析，以检查MEG源估计是否可以恢复源脑区的皮质电流模式所代表的信息内容。分类分析表明，相应的人工实验条件准确地预测模式的皮质电流估计在源脑区。然而，准确的预测也可能来自原始来源不明的大脑区域。探照灯解码进一步揭示，这种意想不到的预测可能跨越原始源位置之外的广泛大脑区域，表明原始源中包含的信息可以通过MEG源估计传播。这种“信息扩散”现象在结合MEG源估计和分类分析来识别代表目标信息的脑区时可能容易导致假阳性解释。真实的脑磁图数据分析还表明，在高级视觉皮层中，呈现的刺激能够以与初级视觉皮层相同的潜伏期被预测，这也表明发生了信息传播。这些结果表明，仔细检查是必要的，以避免假阳性解释时，脑磁源估计和多元模式分析相结合。
To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of “information spreading” may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined.
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